Assessing dynamic vegetation model parameter uncertainty across Alaskan arctic tundra plant communities.

As the Arctic region moves into uncharted territory under a warming climate, it is important to refine the terrestrial biosphere models (TBMs) that help us understand and predict change. One fundamental uncertainty in TBMs relates to model parameters, configuration variables internal to the model whose value can be estimated from data. We incorporate a version of the Terrestrial Ecosystem Model (TEM) developed for arctic ecosystems into the Predictive Ecosystem Analyzer (PEcAn) framework. PEcAn treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We examined how variation in 21 parameters in the equation for gross primary production influenced model sensitivity and uncertainty in terms of two carbon fluxes (net primary productivity and heterotrophic respiration) and two carbon (C) pools (vegetation C and soil C). We set up different parameterizations of TEM across a range of tundra types (tussock tundra, heath tundra, wet sedge tundra, and shrub tundra) in northern Alaska, along a latitudinal transect extending from the coastal plain near Utqiagvik to the southern foothills of the Brooks Range, to the Seward Peninsula. TEM was most sensitive to parameters related to the temperature regulation of photosynthesis. Model uncertainty was mostly due to parameters related to leaf area, temperature regulation of photosynthesis, and the stomatal responses to ambient light conditions. Our analysis also showed that sensitivity and uncertainty to a given parameter varied spatially. At some sites, model sensitivity and uncertainty tended to be connected to a wider range of parameters, underlining the importance of assessing tundra community processes across environmental gradients or geographic locations. Generally, across sites, the flux of net primary productivity (NPP) and pool of vegetation C had about equal uncertainty, while heterotrophic respiration had higher uncertainty than the pool of soil C. Our study illustrates the complexity inherent in evaluating parameter uncertainty across highly heterogeneous arctic tundra plant communities. It also provides a framework for iteratively testing how newly collected field data related to key parameters may result in more effective forecasting of Arctic change.

Effects of alder- and salmon-derived nutrients on aquatic bacterial community structure and microbial community metabolism in subarctic lakes.

Alder (Alnus spp.) and Pacific salmon (Oncorhynchus spp.) provide key nutrient subsidies to freshwater systems. In southwestern Alaska, alder-derived nutrients (ADNs) are increasing as alder cover expands in response to climate warming, while climate change and habitat degradation are reducing marine-derived nutrients (MDNs) in salmon-spawning habitats. To assess the relative influences of ADN and MDN on aquatic microbial community structure and function, we analyzed lake chemistry, bacterial community structure, and microbial metabolism in 13 lakes with varying alder cover and salmon abundance in southwestern Alaska. We conducted bioassays to determine microbial nutrient limitation and physical factors modulating microbial response to nutrient inputs (+N, +P and +NP treatments). Seasonal shifts in bacterial community structure (F = 7.47, P < 0.01) coincided with changes in lake nitrogen (N) and phosphorus (P) concentrations (r2 = 0.19 and 0.16, both P < 0.05), and putrescine degradation (r2 = 0.13, P = 0.06), suggesting the influx and microbial use of MDN. Higher microbial metabolism occurred in summer than spring, coinciding with salmon runs. Increased microbial metabolism occurred in lakes where more salmon spawned. Microbial metabolic activity was unrelated to alder cover, likely because ADN provides less resource diversity than MDN. When nutrients were added to spring samples, there was greater substrate use by microbial communities from lakes with elevated Chl a concentrations and large relative catchment areas (ß estimates for all treatments > 0.56, all P < 0.07). Thus, physical watershed and lake features mediate the effects of nutrient subsidies on aquatic microbial metabolic activity.

Plant-microbial competition for nitrogen increases microbial activities and carbon loss in invaded soils.

Many invasive plant species show high rates of nutrient acquisition relative to their competitors. Yet the mechanisms underlying this phenomenon, and its implications for ecosystem functioning, are poorly understood, particularly in nutrient-limited systems. Here, we test the hypothesis that an invasive plant species (Microstegium vimineum) enhances its rate of nitrogen (N) acquisition by outcompeting soil organic matter-degrading microbes for N, which in turn accelerates soil N and carbon (C) cycling. We estimated plant cover as an indicator of plant N acquisition rate and quantified plant tissue N, soil C and N content and transformations, and extracellular enzyme activities in invaded and uninvaded plots. Under low ambient N availability, invaded plots had 77% higher plant cover and lower tissue C:N ratios, suggesting that invasion increased rates of plant N acquisition. Concurrent with this pattern, we observed significantly higher mass-specific enzyme activities in invaded plots as well as 71% higher long-term N availability, 21% lower short-term N availability, and 16% lower particulate organic matter N. A structural equation model showed that these changes were interrelated and associated with 27% lower particulate organic matter C in invaded areas. Our findings suggest that acquisition of N by this plant species enhances microbial N demand, leading to an increased flux of N from organic to inorganic forms and a loss of soil C. We conclude that high N acquisition rates by invasive plants can drive changes in soil N cycling that are linked to effects on soil C.

Grass invasion effects on forest soil carbon depend on landscape-level land use patterns.

Plant invasions can alter the quality and quantity of detrital and root-derived inputs entering a system, thereby influencing the activities of microbial decomposers and affecting the soil carbon cycle. The effect of these inputs on soil carbon storage is often conflicting, suggesting strong context dependency in the plant-decomposer relationship. Whether there is a generalizable pattern that explains this dependency remains relatively unexplored. Here, we (1) examine how invasion by the exotic grass Microstegium vimineum affects carbon cycling across a land use gradient, and (2) evaluate the importance of inorganic nitrogen availability and other environmental variables for explaining patterns in soil carbon. Using paired invaded and uninvaded plots, we quantified invasion effects on belowground carbon pools, extracellular enzyme activities, and native leaf litter decomposition in forests embedded in an urban, agricultural, or forested landscape matrix. Compared to the urban matrix, invasion-associated declines in total soil organic carbon in the forested and agricultural landscapes were 3.5 and 2.5 times greater, respectively. Inorganic nitrogen availability and M. vimineum biomass interacted to explain these patterns: when both nitrogen availability and M. vimineum biomass were high, invaded soils exhibited higher total organic carbon, unchanged particulate organic matter carbon, and higher mineral-associated organic matter carbon compared to adjacent uninvaded soils. Consistent with these patterns, activities of carbon-mineralizing enzymes were lower in invaded than in uninvaded soils when both nitrogen availability and M. vimineum biomass were high. By contrast,. decomposition of native leaf litter was faster when inorganic nitrogen availability and M. vimineum biomass were high. Our findings suggest that, although this invader may accelerate carbon cycling in forest soils, its effects on soil carbon storage largely depend on nitrogen availability and invader biomass, which can be altered by landscape-level patterns of land use. Additional research is needed to determine whether land use or other broad-scale processes such as atmospheric nitrogen deposition can explain context dependence in plant invasion effects on other ecosystem processes.

Local-scale biotic interactions embedded in macroscale climate drivers suggest Eltonian noise hypothesis distribution patterns for an invasive grass.

A hierarchical view of niche relations reconciles the scale-dependent effects of abiotic and biotic processes on species distribution patterns and underlies most current approaches to distribution modeling. A key prediction of this framework is that the effects of biotic interactions will be averaged out at macroscales - an idea termed the Eltonian noise hypothesis (ENH). We test this prediction by quantifying regional variation in local abiotic and biotic niche relations and assess the role of macroclimate in structuring biotic interactions, using a non-native invasive grass, Microstegium vimineum, in its introduced range. Consistent with hierarchical niche relations and the ENH, macroclimate structures local biotic interactions, while local abiotic relations are regionally conserved. Biotic interactions suppress M. vimineum in drier climates but have little effect in wetter climates. A similar approach could be used to identify the macroclimatic conditions under which biotic interactions affect the accuracy of local predictions of species distributions.

Differences in forest plant functional trait distributions across land-use and productivity gradients.

PREMISE OF STUDY: Plant functional traits are commonly used as proxies for plant responses to environmental challenges, yet few studies have explored how functional trait distributions differ across gradients of land-use change. By comparing trait distributions in intact forests with those across land-use change gradients, we can improve our understanding of the ways land-use change alters the diversity and functioning of plant communities. METHODS: We examined how the variation and distribution of trait values for seven plant functional traits differ between reference natural forest and three types of land-use conversion (pasture, old-field, or "legacy" sites-regrowth following logging), landscape productivity (NPP) and vegetation strata (tree or non-tree "understory"), in a meta-analysis of studies from 15 landscapes across five continents. KEY RESULTS: Although trait variation often differed between land-uses within a landscape, these patterns were rarely consistent across landscapes. The variance and distribution of traits were more likely to differ consistently between natural forest and land-use conversion categories for understory (non-tree) plants than for trees. Landscape productivity did not significantly alter the difference in trait variance between natural forest and land-use conversion categories for any trait except dispersal. CONCLUSIONS: Our results suggest that even for traits well linked to plant environmental response strategies, broad classes of land-use change and landscape productivity are not generally useful indicators of the mechanisms driving compositional changes in human-modified forest systems.

Nitrogen uptake and preference in a forest understory following invasion by an exotic grass.

Plant-soil interactions have been proposed as a causative mechanism explaining how invasive plant species impact ecosystem processes. We evaluate whether an invasive plant influences plant and soil-microbe acquisition of nitrogen to elucidate the mechanistic pathways by which invaders might alter N availability. Using a (15)N tracer, we quantify differences in nitrogen uptake and allocation in communities with and without Microstegium vimineum, a shade-tolerant, C(4) grass that is rapidly invading the understories of eastern US deciduous forests. We further investigate if plants or the microbial biomass exhibit preferences for certain nitrogen forms (glycine, nitrate, and ammonium) to gain insight into nitrogen partitioning in invaded communities. Understory native plants and M. vimineum took up similar amounts of added nitrogen but allocated it differently, with native plants allocating primarily to roots and M. vimineum allocating most nitrogen to shoots. Plant nitrogen uptake was higher in invaded communities due primarily to the increase in understory biomass when M. vimineum was present, but for the microbial biomass, nitrogen uptake did not vary with invasion status. This translated to a significant reduction (P < 0.001) in the ratio of microbial biomass to plant biomass nitrogen uptake, which suggests that, although the demand for nitrogen has intensified, microbes continue to be effective nitrogen competitors. The microbial biomass exhibited a strong preference for ammonium over glycine and nitrate, regardless of invasion status. By comparison, native plants showed no nitrogen preferences and M. vimineum preferred inorganic nitrogen species. We interpret our findings as evidence that invasion by M. vimineum leads to changes in the partitioning of nitrogen above and belowground in forest understories, and to decreases in the microbial biomass, but it does not affect the outcome of plant-microbe-nitrogen interactions, possibly due to functional shifts in the microbial community as a result of invasion.

Land-use intensification reduces functional redundancy and response diversity in plant communities.

Ecosystem resilience depends on functional redundancy (the number of species contributing similarly to an ecosystem function) and response diversity (how functionally similar species respond differently to disturbance). Here, we explore how land-use change impacts these attributes in plant communities, using data from 18 land-use intensity gradients that represent five biomes and > 2800 species. We identify functional groups using multivariate analysis of plant traits which influence ecosystem processes. Functional redundancy is calculated as the species richness within each group, and response diversity as the multivariate within-group dispersion in response trait space, using traits that influence responses to disturbances. Meta-analysis across all datasets showed that land-use intensification significantly reduced both functional redundancy and response diversity, although specific relationships varied considerably among the different land-use gradients. These results indicate that intensified management of ecosystems for resource extraction can increase their vulnerability to future disturbances.

Closed depressions and soil phosphorus influence subsurface phosphorus losses in a tile-drained field in Illinois.

Artificial subsurface (tile) drainage systems can convey phosphorus (P) from agricultural fields to surface waters; however, controls of subsurface dissolved reactive P (DRP) losses at the sub-field scale are not fully understood. We characterized subsurface DRP loads and flow-weighted mean concentration (FWMC) from January 2015 through September 2017 to determine seasonal (growing vs. non-growing) patterns from 36 individually monitored plots across a farm under a corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] rotation in east-central Illinois. Using linear mixed models, we investigated the effects of soil test P (STP), depression depth, and their interaction with precipitation and P fertilization on subsurface DRP losses. Dissolved reactive P loads in drainage tiles increased with precipitation and were greatest during the non-growing season (NGS) in 2016 and 2017. Annual subsurface DRP loads were positively related to STP, and during the NGS, there was a positive relationship between depression depth quantified at the plot-scale and subsurface DRP loads and FWMC. Along a depression-depth gradient, piecewise regression displayed a threshold at a depth of 0.38 m at which STP increased, indicating soil P accumulation in deeper closed depressions. Our study highlights the need to identify areas with the greatest risk of subsurface P losses to implement sub-field scale nutrient management practices.

Stochastic disturbance regimes alter patterns of ecosystem variability and recovery.

Altered ecosystem variability is an important ecological response to disturbance yet understanding of how various attributes of disturbance regimes affect ecosystem variability is limited. To improve the framework for understanding the disturbance regime attributes that affect ecosystem variability, we examine how the introduction of stochasticity to disturbance parameters (frequency, severity and extent) alters simulated recovery when compared to deterministic outcomes from a spatially explicit simulation model. We also examine the agreement between results from empirical studies and deterministic and stochastic configurations of the model. We find that stochasticity in disturbance frequency and spatial extent leads to the greatest increase in the variance of simulated dynamics, although stochastic severity also contributes to departures from the deterministic case. The incorporation of stochasticity in disturbance attributes improves agreement between empirical and simulated responses, with 71% of empirical responses correctly classified by stochastic configurations of the model as compared to 47% using the purely deterministic model. By comparison, only 2% of empirical responses were correctly classified by the deterministic model and misclassified by stochastic configurations of the model. These results indicate that stochasticity in the attributes of a disturbance regime alters the patterns and classification of ecosystem variability, suggesting altered recovery dynamics. Incorporating stochastic disturbance processes into models may thus be critical for anticipating the ecological resilience of ecosystems.

Impacts of Arctic Shrubs on Root Traits and Belowground Nutrient Cycles Across a Northern Alaskan Climate Gradient.

Deciduous shrubs are expanding across the graminoid-dominated nutrient-poor arctic tundra. Absorptive root traits of shrubs are key determinants of nutrient acquisition strategy from tundra soils, but the variations of shrub root traits within and among common shrub genera across the arctic climatic gradient are not well resolved. Consequently, the impacts of arctic shrub expansion on belowground nutrient cycling remain largely unclear. Here, we collected roots from 170 plots of three commonly distributed shrub genera (Alnus, Betula, and Salix) and a widespread sedge (Eriophorum vaginatum) along a climatic gradient in northern Alaska. Absorptive root traits that are relevant to the strategy of plant nutrient acquisition were determined. The influence of aboveground dominant vegetation cover on the standing root biomass, root productivity, vertical rooting profile, as well as the soil nitrogen (N) pool in the active soil layer was examined. We found consistent root trait variation among arctic plant genera along the sampling transect. Alnus and Betula had relatively thicker and less branched, but more frequently ectomycorrhizal colonized absorptive roots than Salix, suggesting complementarity between root efficiency and ectomycorrhizal dependence among the co-existing shrubs. Shrub-dominated plots tended to have more productive absorptive roots than sedge-dominated plots. At the northern sites, deep absorptive roots (>20 cm depth) were more frequent in birch-dominated plots. We also found shrub roots extensively proliferated into the adjacent sedge-dominated plots. The soil N pool in the active layer generally decreased from south to north but did not vary among plots dominated by different shrub or sedge genera. Our results reveal diverse nutrient acquisition strategies and belowground impacts among different arctic shrubs, suggesting that further identifying the specific shrub genera in the tundra landscape will ultimately provide better predictions of belowground dynamics across the changing arctic.

Disturbance-driven changes in the variability of ecological patterns and processes.

Understanding how disturbance shapes the dynamics of ecological systems is of fundamental importance in ecology. One emerging approach to revealing and appreciating disturbance effects involves examining disturbance-driven changes in the variability of ecological responses. Variability is rarely employed as a response variable to assess the influence of disturbance, but recent studies indicate that it can be an extremely sensitive metric, capturing differences obscured by averaging and conveying important ecological information about underlying causal processes. In this paper, we present a conceptual model to understand and predict the effects of disturbance on variability. The model estimates qualitative changes in variability by considering disturbance extent, frequency and intensity, as well as ecosystem recovery, and thereby captures not only the immediate effects of disturbance but also those that arise over time due to the biotic response to an event. We evaluate how well the model performs by comparing predictions with empirical results from studies examining a wide variety of disturbances and ecosystems, and discuss factors that may modify or even confound predictions. We include a concise guide to characterizing and detecting changes in variability, highlighting the most common and easily applied methods and conclude by describing several future directions for research. By considering variability as a response to disturbance, we gain another metric of fundamental system behaviour, an improved ability to identify organizing features of ecosystems and a better understanding of the predictability of disturbance-driven change - all critical aspects of assessing ecosystem response to disturbance.

Microbial community variation and its relationship with nitrogen mineralization in historically altered forests.

Past land use can impart soil legacies that have important implications for ecosystem function. Although these legacies have been linked with microbially mediated processes, little is known about the long-term influence of land use on soil microbial communities themselves. We examined whether historical land use affected soil microbial community composition (lipid profiles) and whether community composition was related to potential net nitrogen (N) mineralization rates in southern Appalachian (USA) forest stands abandoned from agriculture or logging and reforested >50 yr ago. Microbial community composition was determined by a hybrid procedure of phospholipid fatty acid (PLFA) and fatty acid methyl ester (FAME) analysis. We found that community composition varied significantly with past land use. Communities in formerly farmed stands had a higher relative abundance of markers for gram-negative bacteria and a lower abundance of markers for fungi compared with previously logged and reference (i.e., no disturbance history) stands. Potential net N mineralization rates were negatively correlated with fungal and gram-negative bacterial markers in both farmed and reference stands, and fungal abundance and soil bulk density effectively predicted mineralization rates in all stands. Our results indicate that the alteration of microbial communities by historical land use may influence the ecosystem processes they mediate. This is in contrast to typical expectations about microbial community resilience to change. Here, the decrease in fungal abundance observed from disturbance appeared to result in decreased nitrogen mineralization over the long term.